Greedy Heuristics for Minimization of Number of Terminal Nodes in Decision Trees

被引：0
|
作者：
Hussain, Shahid [1 ]
机构：
[1] King Abdullah Univ Sci & Technol, Comp Elect & Math Sci & Engn Div, Thuwal 239556900, Saudi Arabia
来源：
2014 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING (GRC) | 2014年
关键词：
Decision trees; greedy heuristics; number of terminal nodes; Friedman test; Nemenyi ad hoc tests;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper describes, in detail, several greedy heuristics for construction of decision trees. We study the number of terminal nodes of decision trees, which is closely related with the cardinality of the set of rules corresponding to the tree. We compare these heuristics empirically for two different types of datasets (datasets acquired from UCI ML Repository and randomly generated data) as well as compare with the optimal results obtained using dynamic programming method.
引用
收藏
页码：112 / 115
页数：4
相关论文
共 50 条
  • [1] Total path length and number of terminal nodes for decision trees
    Hussain, Shahid
    KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS 18TH ANNUAL CONFERENCE, KES-2014, 2014, 35 : 514 - 521
  • [2] Minimizing Number of Nodes in Decision Trees with Hypotheses
    Azad, Mohammad
    Chikalov, Igor
    Hussain, Shahid
    Moshkov, Mikhail
    KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KSE 2021), 2021, 192 : 232 - 240
  • [3] On greedy heuristics for steiner minimum trees
    Algorithmica (New York), 4 (381):
  • [4] ON GREEDY HEURISTICS FOR STEINER MINIMUM TREES
    DU, DZ
    ALGORITHMICA, 1995, 13 (04) : 381 - 386
  • [5] On Greedy Algorithms for Decision Trees
    Cicalese, Ferdinando
    Jacobs, Tobias
    Laber, Eduardo
    Molinaro, Marco
    ALGORITHMS AND COMPUTATION, PT 2, 2010, 6507 : 206 - +
  • [6] Learning Decision Trees for the Analysis of Optimization Heuristics
    Chiarandini, Marco
    LEARNING AND INTELLIGENT OPTIMIZATION, 2010, 6073 : 208 - 211
  • [7] Heuristics and experimental design for bigraph crossing number minimization
    Stallmann, M
    Brglez, F
    Ghosh, D
    ALGORITHM ENGINEERING AND EXPERIMENTATION, 1999, 1619 : 74 - 93
  • [8] Geometric Heuristics for Transfer Learning in Decision Trees
    Chaubal, Siddhesh
    Rzepecki, Mateusz
    Nicholson, Patrick K.
    Piao, Guangyuan
    Sala, Alessandra
    PROCEEDINGS OF THE 30TH ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT, CIKM 2021, 2021, : 151 - 160
  • [9] Minimization of decision trees is hard to approximate
    Sieling, D
    18TH IEEE ANNUAL CONFERENCE ON COMPUTATIONAL COMPLEXITY, PROCEEDINGS, 2003, : 84 - 92
  • [10] Minimization of decision trees is hard to approximate
    Sieling, Detlef
    JOURNAL OF COMPUTER AND SYSTEM SCIENCES, 2008, 74 (03) : 394 - 403
12345